disrupting software development

Disrupting Software Development-Major Trends Shaping the Evolution of Platform Stacks

For more than a decade, there’s been a series of breakthroughs, a mini-revolution of sorts disrupting software development.

Every aspect of software development has been affected – the tools, the languages and the platforms.

Over this time, we’ve seen an evolution, perhaps a revolution that is approaching, dare I say it, a paradigm shift.

Digital Transformation: Built on a Foundation of Disrupting Software Development

Open source software development, infrastructure disruption and re-assembly, machine learning, and customer-first design are emerging as part of a perfect storm shaping current wave of digital transformation.

The way we assemble components and services to build applications and the way we deliver those applications has all changed.

The industry has seen cloud platforms enabling new, complex business models in 2017 than many analyst and advisory firms predicted.

The growth is unprecedented and, where some may have speculated on the size of this growth, it’s probably fair to say, they underestimated it – wildly!

An entire economy has grown to support cloud platform stacks.

In the marketing technology (martech) space, the number of platforms (depicted by the number of logos) has grown – from around 150 in 2011 to more than 3,500 in 2016.

disrupting software development

Image courtesy of chiefmartec.com

And, while the diagram above reflects growth in marketing technologies, software functionality is driving deeper into and disrupting every aspect of commercial and consumer life.

Software Development is Business Development

The idea that all businesses are software businesses should not come as a surprise to anyone at this point, but what may come as a surprise is that the changes emerging from software development, operations, and data teams—and frankly, you and your team—are at the epicentre of this transformation!

As a technology professional, you are really transforming how enterprise is run—providing data to stakeholders to make better, informed decisions, shaping how customers interact with the business, and ensuring its stability, security, and scalability.

It’s thanks largely to the adoption of public cloud services that Gartner predicts will grow 18% in 2017 to $246.8B, up from $209.2B in 2016.

Billions of Users. Billions of Transactions

The scale at which data is collected, transferred and analysed is now at a scale that was unfathomable less than a decade ago.

It is indeed a technological achievement that lies at the heart of the disruption we’re observing in software development.

Internet of Things (IoT), interconnectivity of networks and devices, web services and how these objects collect and exchange data have all both enabled and been the beneficiaries of disruptive software development practices.

Software needs to run at a scale never seen before by government or industry.

As a result, new tools enabling rapid cloud scaling are evolving to enable incremental growth without changing architecture or making a commitment to high fixed costs in advance.

Commercially, this means being able to fix problems fast, introduce new features fast and to handle failures transparently at scale.

In order to achieve this, a new level automation is needed to not only be able to deploy things into production quickly but also to manage hundreds even thousands of instances of servers and services and to load balance between these.

Machine Learning-Truly Disruptive Software

Machine learning is proving to be a key driver of value for businesses that are able to truly embed it in their daily operations.

Where 20 years ago, widespread commercial applications machine learning was a “pipe dream”, the field has heated up again.

With impressive advancements in resource efficiency, talented researchers have more time to tackle the most complex innovation, rather than spend time on mundane tasks.

Initiatives such as OpenAI, Watson and Tensor Flow and a range of lesser-known, specialised technologies are giving rise to a wealth of excitement around new products (Alexa, Echo & HomePod) and new usage scenarios (voice-driven apps/smart chatbots).

When coupled with the power of having volumes of big, open data sets, we see businesses aiding consumers in ways that were not possible just a short time ago.

Data-hungry, machine-learning software is already having a significant impact on how businesses are making decisions and how information is being delivered.

And, this has driven changes in how software engineering and operations teams function.

Go Lean or Go Home

To cope with the acceleration of business, software development has had to become more agile.

Software applications used to be monolithic. Now they’re made up of tiny components linked by APIs.

Developers are doing sprints in two- or three-week cycles rather than an 18- to 24-month waterfall project where they have to wait for everything to be finished before a new application is launched.

That’s a major disruptor to software development!

With the DevOps movement, now more than ever software developers are more involved with business decisions.

They may not necessarily be company leaders, but they’re not grunts and squints that have had to do what they’re told and produce an application in 12 months.

It’s a much more collaborative and agile process between the developers and operations people.

The skills and expertise of these two groups has unified the development and operational stages of growing software.

“DevOps allows us to work in the agile space directly with Clients where continuous improvement is made possible, especially with the process of real-time analytics and server monitoring” – Collaboration, Facilitated by DevOps, lies at the Heart of Client Successes

Semantia creates disruptive software that supports business transformation. Find out more by calling <strong>1300 766 328</strong> or fill out the form on our get started page.

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